Data and analytics in insurance Evolving trends in data and analytics allow insurers to learn more about customers and deliver better products.
THE INSUR ANCE INDUS TRY has advanced into the next stages of digital transformation. McKinsey spoke with Violet Chung, a partner in the Hong Kong office, to learn more about data and analytics in insurance and what insurance carriers should do to succeed.
McKinsey:
What are some major digital and analytics trends you are seeing in the insurance world?
Given the nature of insurance—the large capital reserve to offset pooled risks, stringent regulation, proprietary claims data, and underwriting know-how—digital disruptors have largely been kept at bay historically. But we are seeing technology trends bleeding into insurance.
For example, applied AI is forcing insurers to view customers as distinct individuals with specific customer journeys and demands for products. As a result, we are seeing scaled personalization in distribution, underwriting, claims, and service to enable tai
Violet Chung:
experiences based on individual preferences.
Also, the maturing of cloud and distributed infrastructure is forcing incumbents to migrate out of legacy on-premise servers and into a cloud environment in order to benefit from the scalability and speed of development. Players that embraced cloud environments early are benefiting from faster turnaround with new product launches.
Because of these and other trends—such as the prevalence of 5G networks, more sophisticated automation and virtualization, trusted architecture— the foundation of insurance is changing. We expect three major shifts:
First, insurance products will be designed for individuals with “pay as you go” models, where premiums, benefits, or both will change dynamically based on individual behavior. Second, drastic shifts in risk profile, from human-caused risks to technology malfunctions and cyberattacks, will require a new calculus on risk and premium. And finally, insurers will more or less automatically underwrite a much wider range of risks using real-world, real-time data from a variety of sources.
McKinsey:
Where will technology have the biggest effects for insurers?
Adopting technology could have both immediate and long-lasting impacts on the following three areas:
First, customer relationships. Customer relationing
Violet Chung:
ships will be redefined as more customer interactions happen through digital channels and insurers reap the resulting dynamic customer insights. What insurance companies know about customer journeys will significantly change, affecting business models and competitive landscapes.
Second, product innovation. Customers will be embedded into “human in the loop” optimization processes empowered by AI. Companies with access to customer behavior data will uniquely benefit from this iterative process by being able to produce better-fitting products and to bring concepts to market more quickly. With enough customer data, insurers can eventually offer tailored solutions that combine multiple insurance products— for example, property and casualty (P&C), health, and life—with dynamic pricing of premiums and benefits that harness insights from individual customers.
Third, value chain evolution. Technology adoption will inevitably make some companies significantly more competitive than others, resulting in a redrawing of the competitive landscape. Traditional roles throughout the value chain may shift, and some players may become more specialized. At the same time, players that manage to build a strong moat in specialized fields will expand to other niche spaces and redistribute the entire industry’s value pool.
McKinsey:
How should insurance players prepare for these digital changes?
Insurers can take four actions:
Work to deliver intelligent and personalized experiences seamlessly through a mix of proprietary and partner ecosystem channels.
Deploy AI-powered capabilities at scale, such as machine learning models and tools, digital marketing, and end-to-end digitalization capabilities to drive automated decision making across the life cycle.
Strengthen their core technology backbone to enable speed, flexibility, and scalability across the enterprise stack.
Rewire traditional teams to operate as platforms, while adopting new ways of working and modern talent practices to enable a culture of innovation.
Violet Chung: